Signal Processing for Communication Systems
Mathuranathan Error Vector Magnitude (EVM) is a key performance metric in communication systems, particularly in digital modulation schemes. It quantifies the difference between the actual transmitted signal and the received signal, thereby measuring the quality of the transmitted signal. EVM is expressed as a percentage or in decibels (dB). Applications of EVM EVM is a crucial … Read more
Key focus : Convolutional codes: Error-correcting codes effective in noisy channels and burst error correction. Know about sliding window & shift registers and how they are used in a convolutional encoder. Linear block codes Linear block codes, like Hamming codes, are mainly employed in hard decision decoding, utilizing the inherent algebraic structure of the code … Read more
OFDM, known as Orthogonal Frequency Division Multiplexing, is a digital modulation technique that divides a wideband signal into several narrowband signals. By doing so, it elongates the symbol duration of each narrowband signal compared to the original wideband signal, effectively minimizing the impact of time dispersion caused by multipath delay spread. OFDM is categorized as … Read more
5G standardization: Collaborative effort between 3GPP and ITU, ensuring global interoperability and compatibility for next-gen mobile networks. ITU ITU stands for the International Telecommunication Union. It is a specialized agency of the United Nations responsible for the development and coordination of international telecommunications standards and regulations. The ITU plays a crucial role in ensuring global … Read more
Key focus: Bandwidth Part (BWP): Allocates segments of spectrum for flexible resource allocation in 5G NR networks, enhancing efficiency and adaptability. Know the difference between bandwidth part and transmission bandwidth Introduction The 3rd Generation Partnership Project (3GPP), in its Release 15, specified the new radio-access technology called 5G New Radio (5G NR). The 5G NR … Read more
Key focus: machine learning, introduction, basics, beginners, algorithms, applications, concepts Introduction Machine learning has emerged as a groundbreaking technology that is transforming industries and reshaping our interaction with technology. From personalized recommendations to autonomous vehicles, machine learning algorithms play a pivotal role in these advancements. If you’re new to the field, this comprehensive beginner’s guide … Read more
Keywords: Markov Chain, Python, probability, data analysis, data science Markov Chain Markov chain is a probabilistic models that describe a sequence of observations whose occurrence are statistically dependent only on the previous ones. This article is about implementing Markov chain in Python Markov chain is described in one of the earlier posts. For better understanding … Read more
Keywords: machine learning, topics, probability, statistics, linear algebra, data preprocessing, supervised learning, unsupervised learning, deep learning, reinforcement learning, model evaluation, cross-validation, hyperparameter tuning. Why the buzz ? Machine learning has been generating a lot of buzz in recent years due to its ability to automate tasks that were previously thought to be impossible or required … Read more
Keywords: Spectrogram, signal processing, time-frequency analysis, speech recognition, music analysis, frequency domain, time domain, python Introduction A spectrogram is a visual representation of the frequency content of a signal over time. Spectrograms are widely used in signal processing applications to analyze and visualize time-varying signals, such as speech and audio signals. In this article, we … Read more
Key focus: Volterra series is an useful tool for modeling nonlinear time invariant systems in general, and they are commonly used to model RF power amplifiers with memory effects Introduction Power amplifier are nonlinear devices responsible for compensating for the signal power loss between a transmitter and receiver. The input power levels to the power … Read more